基于组合赋权的长江上游山洪风险评估——以嘉陵江流域为例

doi:10.11988/ckyyb.20240347

raybet体育在线院报 ›› 2025, Vol. 42 ›› Issue (2): 76-82.DOI: 10.11988/ckyyb.20240347

基于组合赋权的长江上游山洪风险评估——以嘉陵江流域为例

张文婷¹(), 廖婷婷¹(), 张行南¹, 刘永志²^,³, 张涛⁴, 曹雨农¹

¹ 河海大学水文水资源学院,南京 210098
² 南京水利科学研究院水文水资源研究所,南京 210009
³ 水灾害防御全国重点实验室,南京 210098
⁴ 长江水利委员会水文局,武汉 430010

收稿日期:2024-04-07 修回日期:2024-08-08 出版日期:2025-02-01 发布日期:2025-02-01
通信作者:
廖婷婷(1999-),女,广西贵港人,硕士研究生,研究方向为流域防洪及预警。E-mail: 221301010073@hhu.edu.cn
作者简介:
张文婷(1982-),女,江苏泰州人,副教授,博士,主要从事城市水灾害防治和洪水风险等研究。E-mail: zwt@hhu.edu.cn
基金资助:
国家自然科学基金联合基金项目(U2240216); 国家自然科学基金面上项目(42175177); 中国长江电力股份有限公司项目(2423020022)

Flash Flood Risk Assessment in the Upper Yangtze River Based on Combined Weighting: A Case Study of Jialing River Basin

ZHANG Wen-ting¹(), LIAO Ting-ting¹(), ZHANG Xing-nan¹, LIU Yong-zhi²^,³, ZHANG Tao⁴, CAO Yu-nong¹

¹ College of Hydrology and Water Resource, Hohai University, Nanjing 210098, China
² Hydrology and Water Resources Department, Nanjing Hydraulic Research Institute, Nanjing 210009, China
³ State Key Laboratory of Water Hazard Defense,Nanjing 210098, China
⁴ Bureau of Hydrology, Changjiang Water Resources Commission, Wuhan 430010, China

Received:2024-04-07 Revised:2024-08-08 Published:2025-02-01 Online:2025-02-01

摘要/Abstract

摘要：

采用主客观赋权法和博弈论相结合的方法来评估嘉陵江流域的山洪风险。结果显示,4种客观赋权法得到的洪水危险性分布总体相似,但不同方法的风险等级面积占比略有差异,CRITIC权重法识别出更多的高危险性区域。故选择CRITIC权重法、层次分析法和博弈论相结合,形成组合权重评估得到嘉陵江流域山洪综合风险的空间分布。整体而言,嘉陵江流域的山洪风险呈现出自西北向东南递增的趋势,高危险性地区主要分布在四川盆地及其边缘,涉及四川、重庆等22个县区,而低危险性地区则主要位于流域西北部山丘区。影响山洪风险的因素中,年平均降雨、径流深等致灾条件对山洪风险贡献最大,其次是人口密度和国内生产总值(GDP)等社会经济因素,而坡度、地形起伏度等下垫面条件的贡献最低。研究结果对包括嘉陵江流域在内的长江上游流域的山洪管理和应对提供重要参考。

关键词: 山洪, 风险评估, 主客观赋权法, 博弈论, 嘉陵江流域

Abstract:

In this paper, we employed a combination of subjective and objective weighting methods, together with the game theory, to assess flash flood risk in the Jialing River Basin. Results indicate that the flood risk distributions derived from four objective weighting methods are generally consistent, although the proportion of risk levels varies slightly among the methods. Specifically, the CRITIC weighting method identifies more high-risk areas. Therefore, we integrated the CRITIC weighting method, hierarchical analysis, and the game theory to develop a combined weighting assessment, and obtained the comprehensive spatial distribution of flash flood risk in the Jialing River Basin. Overall, flash flood risk exhibits an increasing trend from the northwest to the southeast, with high-risk areas primarily concentrated in the Sichuan Basin and its periphery, encompassing 22 counties and districts in Sichuan and Chongqing. Low-risk areas are predominantly found in the hilly regions of the northwest. Among the factors influencing flash flood risk, mean annual rainfall and runoff depth contribute most significantly, followed by socio-economic factors such as population density and GDP(Gross Domestic Product). Sub-surface conditions, including slope and topographic relief, contribute the least. The findings of this study will serve as a crucial reference for flash flood management and response in the upper Yangtze River Basin, including the Jialing River Basin.

Key words: flash flood, risk assessment, subjective and objective weighting method, game theory, Jialing River Basin

中图分类号:

TV122洪水

张文婷, 廖婷婷, 张行南, 刘永志, 张涛, 曹雨农. 基于组合赋权的长江上游山洪风险评估——以嘉陵江流域为例[J]. raybet体育在线院报, 2025, 42(2): 76-82.

ZHANG Wen-ting, LIAO Ting-ting, ZHANG Xing-nan, LIU Yong-zhi, ZHANG Tao, CAO Yu-nong. Flash Flood Risk Assessment in the Upper Yangtze River Based on Combined Weighting: A Case Study of Jialing River Basin[J]. Journal of Changjiang River Scientific Research Institute, 2025, 42(2): 76-82.

图/表 8

图1 嘉陵江流域地理位置

Fig.1 Geographic location of the Jialing River Basin

图2 嘉陵江流域洪水风险评价体系

Fig.2 Flood risk assessment system for Jialing River Basin

图3 嘉陵江流域洪水风险评价指标因子分布

Fig.3 Distribution of flood risk assessment indicators for the Jialing River Basin

图4 4种客观赋权法结果对比

Fig.4 Comparison of results obtained by four objective weighting methods

图5 4种客观赋权法的风险等级面积占比

Fig.5 Proportions of different risk levels obtained by the four objective weighting methods

图7 3种赋权方法结果与遥感提取结果对比

Fig.7 Comparison of results from three weighting methods with remote sensing extraction results

表1 各方法指标权重结果

Table 1 Weighting results by different methods

指标	影响因子	权重		基于博弈论的组合权重
指标	影响因子	CRITIC 权重法	层次分析法	基于博弈论的组合权重
致灾因子	年平均降雨	0.145	0.200	0.181
致灾因子	径流深	0.153	0.133	0.140
孕灾环境	高程	0.105	0.123	0.116
	坡度	0.111	0.061	0.078
	地形起伏度	0.096	0.063	0.074
	河网密度	0.116	0.041	0.066
	地形湿度指数	0.082	0.029	0.047
	归一化植被指数	0.088	0.018	0.041
承灾体	GDP	0.037	0.143	0.108
	POP	0.029	0.143	0.105
	路网密度	0.038	0.048	0.044

图6 基于博弈论组合赋权的洪水风险评价结果

Fig.6 Flood risk assessment result obtained by the combinatorial weighting method based on the game theory

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基于组合赋权的长江上游山洪风险评估——以嘉陵江流域为例

Flash Flood Risk Assessment in the Upper Yangtze River Based on Combined Weighting: A Case Study of Jialing River Basin

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